Abstract: A method for detecting an influx and/or loss of circulation in a wellbore, comprising measuring a condition in the wellbore using a downhole sensor; determining that a positive displacement pump is shut off or turned on; predicting pit volume and/or gas concentration at a plurality of time points after the positive displacement pump is shut off or turned on using the measured condition in the wellbore prior to the positive displacement pump is shut off or turned on, wherein the measured condition correlates with the pit volume and/or gas concentration; measuring pit volume and/or gas concentration at the plurality of time points; comparing the predicted and the measured pit volumes and/or gas concentrations at the plurality of time points; and producing a warning signal if the difference between the predicted and the measured pit volumes and/or gas concentrations is greater than a pre determined value.

Abstract: A calibration quality associated with a well-drilling apparatus can be determined. A projected value and a calculated value based upon a data set corresponding to a time interval section of a rig state of the well-drilling apparatus can be determined. A difference can be calculated between the projected value and the calculated value. A quality indicator can be applied to the difference, and a calibration quality based upon the application of the quality indicator can be determined.

Abstract: A changepoint detector for modeling data received from at least one sensor in a process in the hydrocarbon industry. The data is segmented into a plurality of segments and for each segment a model is assigned and the data corresponding to the segment fit to that model. A plurality of segmentations are thus provided and these segmentations are evaluated and assigned weights indicative of the fit of the models of the segmentation to the underlying data. The segmentation models are further used to calculate a result that may be input to a process control program.

Abstract: A method for detecting an influx and/or loss of circulation in a wellbore, comprising measuring a condition in the wellbore using a downhole sensor; determining that a positive displacement pump is shut off or turned on; predicting pit volume and/or gas concentration at a plurality of time points after the positive displacement pump is shut off or turned on using the measured condition in the wellbore prior to the positive displacement pump is shut off or turned on, wherein the measured condition correlates with the pit volume and/or gas concentration; measuring pit volume and/or gas concentration at the plurality of time points; comparing the predicted and the measured pit volumes and/or gas concentrations at the plurality of time points; and producing a warning signal if the difference between the predicted and the measured pit volumes and/or gas concentrations is greater than a pre determined value.

Abstract: A method for determining a status of a drill string in a wellbore. The method can include obtaining pressure data and hook load data for the drill string. The pressure data can be filtered to obtain pressure sections. A low pressure threshold can be determined based upon the pressure sections. The hook load data can be filtered to obtain hook load sections. Hook load baselines can be determined based upon the hook load sections. Dynamic thresholds can be determined based upon the hook load baselines. An in-slips status of the drill string can be determined based upon the low pressure threshold, the dynamic thresholds, or both.

Abstract: Systems, methods, and devices are provided for compressing a variety of signals, such as measured signals from a hydrocarbon operation, that may be stored and/or transmitted in compressed form. Segmentation tools and techniques are used to compress the signals. Segmentation techniques include breaking a signal into segments and representing the data samples of the signal as segment boundary points, which may reflect where changes occur in the signal, and segment parameters, which may be utilized to model the segmented data. Embodiments can be used in real-time or in batch modes. New data samples can influence previous segment boundary points and/or segment parameters in some cases. Systems may modify what has already been stored or displayed as a result in revising segmentation information based on analysis utilizing the new data samples. Embodiments may utilize different Bayesian analysis techniques including the use of prior probability distributions and maximum a posteriori analyses.

Abstract: A calibration quality associated with a well-drilling apparatus can be determined. A projected value and a calculated value based upon a data set corresponding to a time interval section of a rig state of the well-drilling apparatus can be determined. A difference can be calculated between the projected value and the calculated value. A quality indicator can be applied to the difference, and a calibration quality based upon the application of the quality indicator can be determined.

Abstract: A method for detecting a drill string washout event. The method includes locating a drill string in a wellbore formed in a subterranean formation. A drilling fluid is pumped into the drill string. The drill string includes a turbine that spins in response to the drilling fluid flowing therethrough. A comparison is made between a rate that the drilling fluid is pumped into the drill string and a spin rate of the turbine. A defect is determined to be formed in the drill string based upon the comparison.

Abstract: A changepoint detector for modeling data received from at least one sensor in a process in the hydrocarbon industry. The data is segmented into a plurality of segments and for each segment a model is assigned and the data corresponding to the segment fit to that model. A plurality of segmentations are thus provided and these segmentations are evaluated and assigned weights indicative of the fit of the models of the segmentation to the underlying data. The segmentation models are further used to calculate a result that may be input to a process control program.

Abstract: A changepoint detector for modeling data received from at least one sensor in a process in the hydrocarbon industry. The data is segmented into a plurality of segments and for each segment a model is assigned and the data corresponding to the segment fit to that model. A plurality of segmentations are thus provided and these segmentations ar evaluated and assigned weights indicative of the fit of the models of the segmentation t the underlying data. The segmentation models are further used to calculate a result that may be input to a process control program.

Abstract: An automotive headlamp (12) having first and second solid-state light sources (44, 46) and a reflector (26) having a light collecting region (28) and an aperture (40) defined therein. The light collecting region (28) of the reflector (26) is adapted to receive and reflect light emitted by the first solid-state light source (44) in a first illumination pattern. The second solid-state light source (46) is adapted to emit light through the aperture (40) in a second illumination pattern.

Abstract: Systems, methods, and devices are provided for compressing a variety of signals, such as measured signals from a hydrocarbon operation, that may be stored and/or transmitted in compressed form. Segmentation tools and techniques are used to compress the signals. Segmentation techniques include breaking a signal into segments and representing the data samples of the signal as segment boundary points, which may reflect where changes occur in the signal, and segment parameters, which may be utilized to model the segmented data. Embodiments can be used in real-time or in batch modes. New data samples can influence previous segment boundary points and/or segment parameters in some cases. Systems may modify what has already been stored or displayed as a result in revising segmentation information based on analysis utilizing the new data samples. Embodiments may utilize different Bayesian analysis techniques including the use of prior probability distributions and maximum a posteriori analyses.

Abstract: A changepoint detector for modeling data received from at least one sensor in a proces in the hydrocarbon industry. The data is segmented into a plurality of segments and fo each segment a model is assigned and the data corresponding to the segment fit to tha model. A plurality of segmentations are thus provided and these segmentations ar evaluated and assigned weights indicative of the fit of the models of the segmentation t the underlying data. The segmentation models are further used to calculate a result tha may be input to a process control program.

Abstract: A method and system is disclosed for automatically detecting the state of a drilling rig during the drilling process of a wellbore. Two or more, but preferably four independent input data channels are received, each input data channel representing a series of measurements made over time during the drilling process. Based on the input channels the most likely state of the drilling rig is detected from at least three possible rig states. The detection method is preferably probabilistic and even more preferably based on particle filtering techniques. The preferred systems and methods disclosed are also capable of detecting events and displaying or notifying drilling personnel of the detected events and suggesting corrective action.

Abstract: A method and system for averting or mitigating undesirable drilling events during a drilling process is disclosed. The state of the drilling rig is detected, preferably automatically, based on surface and/or downhole measurement data. One or more undesirable drilling events are detected by correlating the acquired measurement data with the detected state. A drilling rig action is determined which averts or mitigates a detected undesirable drilling event. Finally, the drilling process is overridden by commanding performance of the action. The algorithm used in detecting the most likely rig state is preferably probabilistic in nature, and is even more preferably based on particle filtering techniques.

Abstract: A method and system is disclosed for automatically detecting the state of a drilling rig during the drilling process of a wellbore. Two or more, but preferably four independent input data channels are received, each input data channel representing a series of measurements made over time during the drilling process. Based on the input channels the most likely state of the drilling rig is detected from at least three possible rig states. The detection method is preferably probabilistic and even more preferably based on particle filtering techniques. The preferred systems and methods disclosed are also capable of detecting events and displaying or notifying drilling personnel of the detected events and suggesting corrective action.

Abstract: A method and system for averting or mitigating undesirable drilling events during a drilling process is disclosed. The state of the drilling rig is detected, preferably automatically, based on surface and/or downhole measurement data. One or more undesirable drilling events are detected by correlating the acquired measurement data with the detected state. A drilling rig action is determined which averts or mitigates a detected undesirable drilling event. Finally, the drilling process is overridden by commanding performance of the action.